1 Introduction

This project delves into analyzing ransomware infections using data extracted from the Shodan API. By analyzing real-time data on internet-connected devices, we explore ransomware trends across various countries and cities. Through data visualizations and statistical analysis, we aim to identify geographic hotspots of ransomware activity, comprehend infection patterns, and provide valuable insights for cybersecurity professionals. The project underscores the importance of monitoring and comprehending ransomware incidents to enhance global cyber defenses.

1.1 Shodan API Overview

The Shodan API, a powerful tool for searching and retrieving data on internet-connected devices, provides information about devices’ locations, services, vulnerabilities, and more. In this project, the API is used to analyze global trends and patterns of ransomware infections.

2 Data Analysis of Ransomware Infections

This section analyzes ransomware infections. It starts with a summary of affected countries and reported incidents. A statistical analysis presents key metrics on infection distribution. The section concludes with a table detailing ransomware incidents by country and city, revealing geographic trends and high-infection areas.

2.1 Ransomware Infections Summary

According to the Shodan dataset, Brazil is the country with the highest number of ransomware infections, with 11 incidents.

There are a total of 108 ransomware infections worldwide!

2.1.1 Statistical Analysis

  • The average number of ransomware infections per country is 2.7
  • The median number of ransomware infections per country is 1
  • The standard deviation of ransomware infections per country is 2.86

2.2 Table of Ransomware Infections by Country and City

This comprehensive table offers a detailed breakdown of ransomware infection rates across various countries and cities. It presents country and city names alongside the corresponding number of ransomware incidents, making it easy to compare regions. This table serves as a crucial reference point for understanding global ransomware trends and identifying areas where cyber defenses may need reinforcement.

Distribution of Ransomware Infections by Country and City
Country City Number of Infections
1095 Germany Frankfurt am Main 5
2030 Russian Federation Moscow 5
1436 Turkey Istanbul 3
2844 Brazil São Paulo 3
2888 China Shanghai 3
556 Turkey Bursa 2
975 Germany Düsseldorf 2
1318 United States Herndon 2
1637 Ukraine Kyiv 2
1844 Brazil Manaus 2
2175 Germany Nürnberg 2
2490 Czechia Prague 2
2822 Mexico Santiago de Querétaro 2
3119 Uzbekistan Tashkent 2
3222 Mexico Villahermosa 2
16 Ghana Accra 1
59 Kazakhstan Almaty 1
118 United States Altamonte Springs 1
124 Brazil Aracruz 1
164 Brazil Araranguá 1
238 United States Ashburn 1
259 Kazakhstan Astana 1
314 Spain Barcelona 1
328 China Beijing 1
364 Brazil Boa Esperança 1
414 France Bourg-en-Bresse 1
443 Belarus Brest 1
481 Argentina Buenos Aires 1
572 Egypt Cairo 1
606 Canada Calgary 1
678 United States Cedar Grove 1
688 China Chengdu 1
743 Moldova, Republic of Chisinau 1
768 China Chongqing 1
801 Argentina Comodoro Rivadavia 1
849 Colombia Cúcuta 1
918 United States Des Moines 1
922 Bangladesh Dhaka 1
1015 Germany Falkenstein 1
1048 China Foshan 1
1121 Argentina Godoy Cruz 1
1161 Argentina Haedo 1
1240 Viet Nam Hanoi 1
1253 Finland Helsinki 1
1337 India Hyderābād 1
1385 Pakistan Islamabad 1
1444 Brazil Itajaí 1
1513 South Africa Johannesburg 1
1555 Taiwan Kaohsiung 1
1577 India Kolkata 1
1664 Nigeria Lagos 1
1718 United States Lee’s Summit 1
1747 Peru Lima 1
1789 Portugal Lisbon 1
1834 Spain Madrid 1
1884 Brazil Marechal Cândido Rondon 1
1929 Colombia Medellín 1
1998 United States Mercerville 1
2057 India Mumbai 1
2110 Russian Federation Novyy Urengoy 1
2142 Mexico Nuevo Laredo 1
2222 Mexico Ojuelos de Jalisco 1
2258 Japan Osaka 1
2290 Czechia Ostrava 1
2331 Denmark Otterup 1
2386 Panama Panamá 1
2426 Panama Panama City 1
2462 Mexico Piedras Negras 1
2548 Poland Radom 1
2598 United States Rancho Santa Margarita 1
2625 Pakistan Rawalpindi 1
2644 Brazil Rio de Janeiro 1
2710 Russian Federation Saint Petersburg 1
2758 United States Santa Fe Springs 1
2767 Chile Santiago 1
2928 China Shenzhen 1
2992 Singapore Singapore 1
3021 Macedonia, Republic of Skopje 1
3045 Bulgaria Sofia 1
3154 Spain Tortosa 1
3161 Argentina Villa Sarmiento 1
3260 Lithuania Vilnius 1
3312 Singapore Woodlands 1
3351 Serbia Zrenjanin 1

3 Data Visualization of Ransomware Infections

This section visualizes ransomware infection patterns globally. It maps incidents at country and city levels using Shodan API data, highlighting affected regions and trends. An interactive map lets users zoom in and examine infection details, making it useful for cybersecurity professionals and researchers.

3.1 Exploring Ransomware Hotspots

This data visualization explores the global distribution of ransomware infections, focusing on the geographical hotspots by country and city. Using data from the Shodan API, the map highlights areas with the highest concentrations of ransomware incidents, shedding light on trends and patterns in cyberattacks. By mapping ransomware infections based on real-time data, the visualization provides insights into which regions are most affected and allows for a better understanding of the geographic spread of these cyber threats. The interactive map enables users to zoom in on specific locations and view detailed information on the number of incidents, cities, and countries impacted, offering valuable insights for cybersecurity professionals and researchers.